I am using the solution for spend analytics and contract analytics. I'm specifically using it to understand if there's any contract leakage. In spend analytics, I'm using it specifically for category management. I design category strategies using multiple dimensions from the spend analysis. We also use it for improvements in supplier relationship management, such as on-time payment.
IBM Cloud Pak for Data
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Great experience for using IBM cloud Pak
What do you like best about the product?
Easy to use
Easy to implement
Good customer support
Provides good features in terms of data security
Easy to integrate with the other systerms.
Good frequency of usuage
Easy to implement
Good customer support
Provides good features in terms of data security
Easy to integrate with the other systerms.
Good frequency of usuage
What do you dislike about the product?
Nothing like a dislike in this product as per my opinion.
What problems is the product solving and how is that benefiting you?
It provides good features like accelerate deployment automations. Manages data effectively and efficiently.
Excellent tool for data aggregation
What do you like best about the product?
It helped me in data aggregation from different sources seamlessly and provided excellent insights. This would be my go to tool now after sure.
What do you dislike about the product?
Over my short use of the application, I couldn't find any.
What problems is the product solving and how is that benefiting you?
It helped me analyzing data from different sources, club them together so I could focus on critical data points.
High level service quality
What do you like best about the product?
Very good level of insights. The quality of the work is really remarkable
What do you dislike about the product?
IBM often overcharges for the service it renders
What problems is the product solving and how is that benefiting you?
Solving for the high level data integrity
Good Experience
What do you like best about the product?
The platform supports the entire data and AI lifecycle, from data ingestion and preparation to model development and deployment. This end-to-end capability can enhance collaboration among data scientists, data engineers, and business analysts.
What do you dislike about the product?
I found it a little complex as a new user, especially for those who are new to the system. The range of features and tools may require a learning curve, and some users may prefer a more straightforward user interface.
What problems is the product solving and how is that benefiting you?
Multiple APIs hit on a single channel.
It is good and have services as per needs.
What do you like best about the product?
It have services that i need for my product.
What do you dislike about the product?
support can be improved. Ease of use can also be improved.
What problems is the product solving and how is that benefiting you?
It helps to provision servers for my system and we are able to get our system running.
One of the best AI-powered data platform in the market
What do you like best about the product?
The platform's UI is super intuitive, making it easy to create customizable dashboards for data analysis. It also provides a plethora of other useful features like data virtualization and containerization which helps in creating an error-free environment and improve the monitoring of the service by capturing insightful data.
What do you dislike about the product?
Nothing major that I can think of but there is definitely a bit of a learning curve which might make you hesitant to start with but the customer support is good.
What problems is the product solving and how is that benefiting you?
It is providing an AI-powered platform for data collection and analysis which can consume data from multiple sources and help create advanced data analysis solutions improving the team's productivity and efficiency.
IBM CP4D- One stop Destination for AI Tech
What do you like best about the product?
I just really love the way how IBM Cp4D has a bunch of features in one tool.
It does data integration/data ingestion, data virtualization,data fabric,Building dashboards and dealing with ML aLgos etc.It's really flexible to use for data integration connecting to a different number of data sources . It's way advanced compared to the tools in market at the moment and very much user friendly . It's a game changer.I am a data engineer formerly worked with IBM where I got to use this amazing tool
It does data integration/data ingestion, data virtualization,data fabric,Building dashboards and dealing with ML aLgos etc.It's really flexible to use for data integration connecting to a different number of data sources . It's way advanced compared to the tools in market at the moment and very much user friendly . It's a game changer.I am a data engineer formerly worked with IBM where I got to use this amazing tool
What do you dislike about the product?
Nothing as such that we can dislike about IBM CP4D.
What problems is the product solving and how is that benefiting you?
As mentioned earlier in the review, Data Integration/Data Ingestion, Data virtualization, Data transformations using SQL etc.
Good for big data management
What do you like best about the product?
It is faster and can load a lot of data without putting much load on the servers. The data is secured.
What do you dislike about the product?
The UI of it is very difficult to navigate. Even the documentation is not easy to follow or easily available.
What problems is the product solving and how is that benefiting you?
My business has a lot of upstream data on-prem. We have to utilise ample amount of warehouses data and connect to IBM DB2 with AWS service for fetching the data. IBM Cliud Pak for data nakes this process efficient and fast.
A scalable data analytics and digital transformation tool that provides useful features and integrations
What is our primary use case?
What is most valuable?
The data sits in silos. DataStage allows me to connect to different data sources. It also allows me to do ETL or ELT. It has a good integration with data warehouses.
What needs improvement?
The product must improve its performance. We see typical cloud-related issues in the solution. IBM can still focus more on keeping the performance up and keeping it 100% available all the time.
For how long have I used the solution?
I have been using the solution for more than a year.
What do I think about the stability of the solution?
I rate the stability a seven out of ten.
What do I think about the scalability of the solution?
The tool is scalable. I rate the scalability an eight out of ten. More than 500 people are using the solution in our organization.
How are customer service and support?
The first line of support is strong enough. I do not have to put in additional effort.
What's my experience with pricing, setup cost, and licensing?
The solution is expensive. It must improve its costs.
What other advice do I have?
I was not fully part of the core team or implementation. The solution is suitable for data analytics and digital transformation. People considering the solution must decide their use case before exploring the tool’s functionalities or components. Typically, people use an IT-heavy approach, adopting functionalities first and then looking for use cases. I would advise them to do the exact opposite.
Whatever we do should be in line with the business purpose and the business vision. We must be mindful of the business model and the organization's maturity to consume the insights. These technologies are targeted towards delivering the right decision-making aids. We should not make it an IT agenda.
Overall, I rate the product a nine out of ten.
Offers powerful data preparation capabilities for creating and providing reliable data for accurate predictions
What is our primary use case?
The last project I worked on was for the World Bank. I was tasked with designing the architecture for an e-commerce system aimed at rural people in Mexico, enabling them to sell products. I handled all the requirements and design aspects. The main focus of the project was the implementation of artificial intelligence and effective data management. I proposed IBM Cloud Pak for Data and an update to the cloud platform.
Unfortunately, the project was not successful in terms of booking the final customer, as the required products were quite expensive. However, I designed the entire structure and architecture. That was one of my most recent projects. Another ongoing project with Cloud Pak is working on sales proposals for various customers in Mexico. The adoption of Cloud Pak for Data in Mexico is relatively slow compared to Data Station and Information Server, which is faster.
The main focus is on projecting sales and managing product renewals in the stores. That's more or less what I'm currently involved with regarding Cloud Pak for Data.
What is most valuable?
Its data preparation capabilities are highly valuable. You need to ensure that the data is properly created and provided in the most reliable format, especially for accurate predictions.
For instance, IBM offers numerous artificial intelligence algorithms that require the data to be in the correct form and with precise information. We need to ingest all the data into the artificial intelligence models. I believe this is one of the primary objectives of IBM Cloud Pak for Data.
What needs improvement?
There are several specific connectors that we need to use, such as the one for SAP or XML. These connectors are not fully integrated into Cloud Pak for Data. However, they are very useful in database and information services for many of the projects I've worked on.
Right now, the product is trying to be more maturity in terms of connectors. That, I believe, is an area where Cloud Pak can improve. Obviously, they are constantly working on refining the product. We are currently on version 4.5, and I have good relationships with some people at IBM.
They are actively striving to iterate and release new versions of the product. They are also focusing on improving Information Server and Rapid Stage 5.
In future releases, it would be beneficial to have more advanced data curation features. Specifically, I'm referring to data analysis and the quality dimensions associated with it. In my experience, this aspect is not as mature in Cloud Pak for Data compared to Information Server or database information analyzer, as they have been working more extensively on these areas.
They have been more focused on developing and enhancing those specific aspects. However, based on my research and discussions with my peers at IBM, I believe these features will be included in Cloud Pak in the near future.
For how long have I used the solution?
I have been using IBM Cloud Pak for Data for three years. The last version I worked with was 4.5.
What do I think about the stability of the solution?
I would rate the stability an eight out of ten. The solution have lot of issues right now.
What do I think about the scalability of the solution?
I would rate the scalability of this solution a nine out of ten.
How are customer service and support?
The customer service and support are good. It is one of the main part of the solution.
How would you rate customer service and support?
Positive
How was the initial setup?
It depends because the IT infrastructure for Cloud Pak for Data is in the cloud. The implementation process is different from traditional system deployments. So, I would say it depends.
I come from many years of working with Data Station and Information Server, which follow a classic implementation approach. However, implementing Cloud Pak is somewhat different. The vision or the concept behind it needs to be approached differently.
What's my experience with pricing, setup cost, and licensing?
It's quite expensive. Small companies cannot afford such a product. It's mainly targeted towards larger companies.
The pricing is very high.
What other advice do I have?
You need to have sufficient funds and experienced personnel because it is a highly technical solution. It's not something that can be easily implemented without proper knowledge and expertise.
For management, I would suggest taking smaller steps and gradually adapting the product within the company. Starting with smaller projects rather than diving into a major implementation.
The solution has a lot of potential, so I would rate it a nine out of ten.
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